4 papers
Convergence of the generalization error for deep gradient flow methods for PDEs
Chenguang Liu, Antonis Papapantoleon, Jasper Rou
The aim of this article is to provide a firm mathematical foundation for the application of deep gradient flow methods (DGFMs) for the solution of (high-dimensional) partial differ…
Time Deep Gradient Flow Method for pricing American options
Jasper Rou
In this research, we explore neural network-based methods for pricing multidimensional American put options under the BlackScholes and Heston model, extending up to five dimensions…
Error Analysis of Deep PDE Solvers for Option Pricing
Jasper Rou
Option pricing often requires solving partial differential equations (PDEs). Although deep learning-based PDE solvers have recently emerged as quick solutions to this problem, thei…
A time-stepping deep gradient flow method for option pricing in (rough) diffusion models
Antonis Papapantoleon, Jasper Rou
We develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approxima…